Generally, thermoforming is used for the production of simple shaped packaging or housing parts, which do not feature any additional functions. However, by the use of heat conductive plastic materials, a heat loss function can be implemented to thermoformed parts. Increased filler contents are correlated with higher heat conductivity. However, higher filler contents also lead to an altered thermoformability of sheets. As a result, simulation becomes more and more important, when operating the thermoforming process at its limits. To obtain high predictive accuracy in thermoforming simulation, material models as well as data fitting methods are needed, which match with the real thermoforming material and process. In this investigation the use of the K-BKZ model for thermoforming simulation of heat conductive plastics is evaluated. Two different kinds of parameter fitting algorithms are examined. On the one hand, the K-BKZ model is fitted by a reverse-engineering procedure using the IKT’s thermoforming-material-characterization as reference test. On the other hand, classic rheology by means of rotational rheometry and the rheotens-test is used for the data fitting of the K-BKZ model parameters. As reference materials two grades of polystyrene (high and low viscosity) combined with two graphite fillers (spherical and platelet) are used. The predictive accuracy of the material model and the two parameter fitting procedures is quantified by a comparison of the simulation with real thermoforming experiments.